1. Field of the Invention
The present invention relates to an image processing apparatus and an image processing method, and more particularly, to an image processing apparatus and an image processing method that perform noise reduction processing on a video signal.
2. Description of Related Art
A video signal is a signal configured with a set of a plurality of frame images picked up at specified time intervals. Generally, it is possible to assume that each frame image is a signal having a correlation with respect to a local space within a frame, and further a neighboring frame is a signal having a correlation with respect to a local time between frames.
The aforementioned video signal can be obtained when, for example, an image of an arbitrary object is picked up using a video camera provided with an image pickup device such as CCD or CMOS, by photoelectrically converting object images formed on the image pickup device via lenses making up an image pickup section of the video camera in units of pixels making up the image pickup device and sequentially outputting the object images. Furthermore, the aforementioned video signal is amplified by an amplifier so as to have a predetermined brightness level and subjected to further processing as a digital image digitized by an A/D converter.
On the other hand, when an image of an object is picked up using the aforementioned video camera, noise ascribable to characteristics of the image pickup device is superimposed on the picked up image. Shot noise ascribable to the statistical nature of photoelectrical conversion accounts for the majority of the aforementioned noise.
Shot noise has average amplitude proportional to the square root of an image signal value, is known to be statistically random noise in a time direction and a spatial direction and appears noticeably when, for example, the amount of gain is increased in compensation for a shortage in amount of image forming light impinging on the image pickup device.
Examples of noise reduction processing on a video signal on which random noise such as the aforementioned shot noise is superimposed may include intra-frame noise reduction processing using a spatial correlation and inter-frame noise reduction processing using a time correlation, Various proposals are conventionally presented about intra-frame noise reduction processing using a spatial correlation and inter-frame noise reduction processing using a time correlation.
As noise reduction processing using a time correlation, for example, recursive noise reduction processing is known which can achieve a large amount of noise reduction by using frames after noise reduction as past frames.
On the other hand, Japanese Patent Application Laid-Open Publication No. 6-62283 describes a technique capable of improving noise reduction performance even on scene changes or scenes with large movement by using both an intra-frame correlation and an inter-frame correlation.
The noise reduction system described in Japanese Patent Application Laid-Open Publication No. 6-62283 has a configuration including an image memory for producing a one-frame or one-field delay, carrying out non-linear filter processing using newly inputted central pixel data, pixel data in the vicinity of the central pixel data and pixel data in the vicinity of the central pixel data in the pixel data one frame or one field before, which has already been recorded in the image memory and subjected to noise reduction, and thereby outputting noise reduced pixel data. According to the non-linear filter processing described in Japanese Patent Application Laid-Open Publication No. 6-62283, large weighting factors are assigned to data of neighboring pixels having a high correlation with the central pixel data, small weighting factors are assigned to pixels having a low correlation with the central pixel data and weighted averaging is performed.
According to the noise reduction system described in aforementioned Japanese Patent Application Laid-Open Publication No. 6-62283, it is possible to perform noise reduction processing using both an intra-frame correlation and an inter-frame correlation. Furthermore, according to the noise reduction system described in aforementioned Japanese Patent Application Laid-Open Publication No. 6-62283, especially when the picked up image is in a stationary condition, as the number of pixels with large weighting factors increases among pixels one frame or one field before and pixels in the current field used for weighted averaging, the number of pixels contributing to averaging increases, and it is thereby possible to effectively perform noise reduction. Furthermore, according to the noise reduction system described in Japanese Patent Application Laid-Open Publication No. 6-62283, when there is a large movement or scene change in a picked up image, larger weighting factors are automatically assigned to pixels in the current field than pixels one frame or one field before, and weighted averaging is performed substantially on pixels in the current field. Therefore, according to the noise reduction system described in Japanese Patent Application Laid-Open Publication No. 6-62283, even when there is a large movement or scene change in a picked up image, a sufficient noise reduction effect can be obtained though the effect is smaller than that in a stationary condition.
On the other hand, as a technique for attempting adaptive control over the structure included in an image and a noise reduction effect within the image, there is a technique described, for example, in Japanese Patent Application Laid-Open Publication No. 2006-229749.
Japanese Patent Application Laid-Open Publication No. 2006-229749 describes a technique that analyzes time correlativity and spatial correlativity, thereby performs texture judgment processing on a pixel to be processed and then adjusts a filter strength of a spatial filter in units of pixels subjected to time filter processing. To he more specific, Japanese Patent Application Laid-Open Publication No 2006-229749 describes a technique that calculates flatness of a target pixel based on texture judgment using pixels in the peripheral region thereof. increases the spatial filter strength when the flatness is large and reduces the spatial filter strength when the flatness is small.
Furthermore, as for a parameter of the filter strength, in the case, for example, of a common r filter, the absolute value of a difference between a target pixel used to judge whether or not to use the pixel as a smoothing pixel and pixels peripheral to the target pixel is used as a threshold. When such a method is used, the parameter of the filter strength is controlled so as to be spatial filter strength appropriate to the structure of the image and blurs of the structure in the image are suppressed and subjective image quality can thereby be improved.